function [Weight_pool, bias_pool, sort_pool,JM_pool] = add_into_pool(InputWeight_temp, InputBias_temp, data_train, Weight_pool, bias_pool, sort_pool,JM_pool,num_bins)
    % 计算 H
    tempH = InputWeight_temp * data_train(:, 2:end)';
    num_train = size(data_train, 1);
    ind = ones(1, num_train);
    BiasMatrix = InputBias_temp(:, ind);
    tempH = tempH + BiasMatrix;
    H = 1 ./ (1 + exp(-tempH));
    H = [data_train(:, 1), H'];
    start_time_train=cputime;
    % 计算 JM 可分性
    %my_distance 一个向量组
%     num_bins = 50;
    Cross_entrophy = cal_CR(H,num_bins);
    Cross_entrophy = 1./Cross_entrophy;
%     MF_dis = cal_manifold_distance(H);
    
    JM_aver_list = cal_JM_aver_list(H);
    JM_aver_list(isnan(JM_aver_list)) = -inf; % 将 NaN 替换为负无穷大
    end_time_train=cputime;
    MF_disTime = end_time_train-start_time_train ;
    % 将权重、偏置和 JM 可分性加入池中
    Weight_pool = [Weight_pool; InputWeight_temp];
    bias_pool = [bias_pool; InputBias_temp];
    sort_pool = [sort_pool; Cross_entrophy];
    JM_pool = [JM_pool; JM_aver_list];
%     sort_pool = [sort_pool; MF_dis];
%     sort_pool = [sort_pool; JM_aver_list];
end
